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Welcome to this week in Neo4j where we round up what’s been happening in the world of graph databases in the last 7 days.

This week we have the World Cup Graph and GraphQL API, an article explaining how to tune Cypher queries by understanding cardinality, querying Spatial data points, and the Intro to Graph Databases YouTube series is back!

All of us in the DevRel team are excited to hear about your experiences, perhaps at a future GraphConnect or Neo4j event.

On behalf of the Neo4j community, thanks for all your work Bea!

The World Cup Graph

We’re well into the 2nd round of matches at World Cup 2018 and Michael and I decided to revive the World Cup Graph that we first created 4 years ago. The dataset contains the matches, players, and tournaments for every World Cup from 1930 to the present day.

If you want to play around with the data we have a hosted version on a Neo4j Cloud instance at c27d992b.databases.neo4j.io. You can login with the username worldcup and password worldcup and then run :play worldcup-2018-queries for a guide that will show you some queries you can run against the dataset.

World Cup GraphQL API

This only took us a few hours thanks to the excellent GRANDstack Starter Kit. All the scaffolding had been done for us – all we had to do was fill in details about our database and create a GraphQL schema.

GRANDstack Hackathon

The World Cup GraphQL API and UI starter can be the foundation for your contribution to the GRANDstack Hackathon which still runs till June 30 and has some cool prizes.

Another set of GraphQL APIs that you can use, is running on top of our graphql community graph. My colleague Michael added these developer community APIs.

Based on popular demand, Ryan this week resumed the Intro to Graph Databases YouTube series with a video explaining the Cypher query language.

Ryan starts by explaining how the developer surface of Neo4j has evolved over the years, from the embedded Java API, via the REST API, up to the present day of Bolt drivers and stored procedures and functions executed via Cypher.

Querying Spatial data points, The Strava Graph, Cypher snippets

Last week we featured a blog post where Rik showed how to import the Open Beer Database along with Spatial data points, and in this week’s blog post he shows how to write queries against this new data type.

Tuning Cypher queries by understanding cardinality

Andrew starts with a high level overview of how Cypher execution works, and then takes us through a worked example from the in built movies dataset, showing various tricks to improve the performance of the query.

If you’ve ever wondered why your queries aren’t doing what you expected them to this is a great post to read.

Author

Mark Needham, Developer Relations Engineer

Mark Needham is a graph advocate and developer relations engineer at Neo4j. As a developer relations engineer, Mark helps users embrace graph data and Neo4j, building sophisticated solutions to challenging data problems. Mark previously worked in engineering on the clustering team, helping to build the Causal Clustering feature released in ... know more